Triple
T2894123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Peau de chagrin |
E63896
|
entity |
| Predicate | firstPublisher |
P7323
|
FINISHED |
| Object | Charpentier |
E225104
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Charpentier | Statement: [La Peau de chagrin, firstPublisher, Charpentier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charpentier Context triple: [La Peau de chagrin, firstPublisher, Charpentier]
-
A.
Charpentier
chosen
Charpentier is a French surname borne by various notable individuals across fields such as science, arts, and politics.
-
B.
Gauthier
Gauthier is a French given name and surname, equivalent to the English name Walter and historically borne by various notable figures in France and other Francophone regions.
-
C.
Roussel
Roussel is a surname of French origin, often used as an alternative spelling of Russell.
-
D.
Ganthier
Ganthier is a commune in western Haiti known for its rural character and proximity to the capital, Port-au-Prince.
-
E.
Charlotte Charpentier
Charlotte Charpentier was the wife of renowned Scottish novelist and poet Sir Walter Scott.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ab4c45822c8190830c5f2bb97bcfd0 |
completed | March 6, 2026, 9:51 p.m. |
| NER | Named-entity recognition | batch_69abe063de6c8190bce9ddefd1dd62e1 |
completed | March 7, 2026, 8:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b031814764819096a1664b468ec817 |
completed | March 10, 2026, 2:58 p.m. |
Created at: March 6, 2026, 10:07 p.m.